Multitask learning (Caruana, 1997) has been found to be an effective method of improving the generalisation performance of classifiers. The recent growth in the use of deep neural network models for speech processing enables multitask learning to be integrated easily into the acoustic model training procedure. In this talk I will discuss practical implementations of multitask learning and present recent work where we have applied the technique to range of problem settings in speech recognition and synthesis.